vignettes/articles/accessing_project_data.Rmd
accessing_project_data.RmdThis article walks through, in detail, accessing data specific to
projects, primarily via mermaid_get_project_data().
To access data related to your MERMAID projects, first obtain a list
of your projects with mermaid_get_my_projects().
At this point, you will have to authenticate to the Collect app. R will help you do this automatically by opening a browser window for you to log in to Collect, either via Google sign-in or username and password - however you normally do!
Once you’ve logged in, come back to R. Your login credentials will be stored for a day, until they expire, and you will need to login again. The package handles the expiration for you, so just log in again when prompted.
library(mermaidr)
my_projects <- mermaid_get_my_projects()
my_projects
#> # A tibble: 19 × 15
#> id name countries num_sites tags notes status data_policy_beltfish
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e6915c-1… TWP … Indonesia 14 "WCS… "" Open Private
#> 2 170e7182-7… 2018… Fiji 10 "WCS… "Thi… Open Private
#> 3 173c2353-3… Copy… Fiji 8 "WCS… "Nam… Open Public Summary
#> 4 1fbdb9ea-9… a2 Canada, … 9 "WWF… "Nam… Open Private
#> 5 2c0c9857-b… Shar… Canada, … 27 "" "dhf… Open Public Summary
#> 6 2d6cee25-c… WCS … Mozambiq… 74 "WCS… "Dat… Open Private
#> 7 3a9ecb7c-f… Aceh… Indonesia 18 "WCS… "" Open Private
#> 8 4080679f-1… Mada… Madagasc… 74 "WCS… "MAC… Open Private
#> 9 4d23d2a1-7… Mada… Madagasc… 16 "WCS… "Mon… Open Public Summary
#> 10 507d1af9-e… Kari… Indonesia 43 "WCS… "" Open Private
#> 11 5679ef3d-b… Mada… Madagasc… 33 "WCS… "" Open Public Summary
#> 12 5f13e6dc-4… Copy… Indonesia 43 "WCS… "" Open Public Summary
#> 13 75ef7a5a-c… Kubu… Fiji 78 "WCS… "" Open Private
#> 14 7a6bfd69-6… Copy… Belize 31 "WCS… "" Open Public Summary
#> 15 9de82789-c… XPDC… Indonesia 37 "" "XPD… Open Private
#> 16 a1b7ff1f-8… Grea… Fiji 76 "Uni… "" Open Private
#> 17 bacd3529-e… Beli… Belize, … 35 "WCS… "" Open Public Summary
#> 18 d065cba4-e… 2019… Fiji 31 "WCS… "Ble… Open Private
#> 19 e1efb1e0-0… 2016… Fiji 8 "WCS… "Nam… Open Private
#> # ℹ 7 more variables: data_policy_benthiclit <chr>,
#> # data_policy_benthicpit <chr>, data_policy_benthicpqt <chr>,
#> # data_policy_habitatcomplexity <chr>, data_policy_bleachingqc <chr>,
#> # created_on <chr>, updated_on <chr>This function returns information on your projects, including project countries, the number of sites, tags, data policies, and more.
To filter for specific projects, you can use the filter
function from dplyr:
library(dplyr)
indonesia_projects <- my_projects %>%
filter(countries == "Indonesia")
indonesia_projects
#> # A tibble: 5 × 15
#> id name countries num_sites tags notes status data_policy_beltfish
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e6915c-1c… TWP … Indonesia 14 "WCS… "" Open Private
#> 2 3a9ecb7c-f9… Aceh… Indonesia 18 "WCS… "" Open Private
#> 3 507d1af9-ed… Kari… Indonesia 43 "WCS… "" Open Private
#> 4 5f13e6dc-40… Copy… Indonesia 43 "WCS… "" Open Public Summary
#> 5 9de82789-c3… XPDC… Indonesia 37 "" "XPD… Open Private
#> # ℹ 7 more variables: data_policy_benthiclit <chr>,
#> # data_policy_benthicpit <chr>, data_policy_benthicpqt <chr>,
#> # data_policy_habitatcomplexity <chr>, data_policy_bleachingqc <chr>,
#> # created_on <chr>, updated_on <chr>Alternatively, you can search your projects using
mermaid_search_my_projects(), narrowing projects down by
name, countries, or tags:
mermaid_search_my_projects(countries = "Indonesia")
#> # A tibble: 7 × 15
#> id name countries num_sites tags notes status data_policy_beltfish
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e6915c-1c… TWP … Indonesia 14 "WCS… "" Open Private
#> 2 2c0c9857-b1… Shar… Canada, … 27 "" "dhf… Open Public Summary
#> 3 3a9ecb7c-f9… Aceh… Indonesia 18 "WCS… "" Open Private
#> 4 507d1af9-ed… Kari… Indonesia 43 "WCS… "" Open Private
#> 5 5f13e6dc-40… Copy… Indonesia 43 "WCS… "" Open Public Summary
#> 6 9de82789-c3… XPDC… Indonesia 37 "" "XPD… Open Private
#> 7 bacd3529-e0… Beli… Belize, … 35 "WCS… "" Open Public Summary
#> # ℹ 7 more variables: data_policy_benthiclit <chr>,
#> # data_policy_benthicpit <chr>, data_policy_benthicpqt <chr>,
#> # data_policy_habitatcomplexity <chr>, data_policy_bleachingqc <chr>,
#> # created_on <chr>, updated_on <chr>Then, you can start to access data about your projects, like project
sites via mermaid_get_project_sites():
indonesia_projects %>%
mermaid_get_project_sites()
#> # A tibble: 155 × 12
#> project id name notes latitude longitude country reef_type reef_zone
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Karimunjawa… a763… Gent… "" -5.86 111. Indone… fringing back reef
#> 2 Copy of Kar… 2458… Gent… "" -5.86 111. Indone… fringing back reef
#> 3 Aceh Jaya C… 5436… Wisa… "" 5.04 95.4 Indone… fringing fore reef
#> 4 Aceh Jaya C… b7d5… Reha… "" 4.84 95.4 Indone… fringing fore reef
#> 5 Karimunjawa… 0368… Meny… "" -5.80 110. Indone… fringing fore reef
#> 6 Copy of Kar… 4f5f… Meny… "" -5.80 110. Indone… fringing fore reef
#> 7 Aceh Jaya C… 38f7… Pula… "" 5.08 95.3 Indone… fringing back reef
#> 8 Karimunjawa… 21ae… Batu… "" -5.81 110. Indone… fringing back reef
#> 9 Karimunjawa… 371b… Tanj… "" -5.83 110. Indone… fringing back reef
#> 10 Karimunjawa… 43d3… Lego… "" -5.87 110. Indone… fringing back reef
#> # ℹ 145 more rows
#> # ℹ 3 more variables: exposure <chr>, created_on <chr>, updated_on <chr>Or the managements for your projects via
mermaid_get_project_managements():
indonesia_projects %>%
mermaid_get_project_managements()
#> # A tibble: 30 × 18
#> project id name name_secondary est_year size parties compliance
#> <chr> <chr> <chr> <chr> <int> <dbl> <chr> <chr>
#> 1 TWP Gili Sulat … 0975… Zona… "Core Zone" 2013 NA govern… full
#> 2 Aceh Jaya Coast… cc92… Core… "" 2019 NA commun… full
#> 3 Aceh Jaya Coast… 1498… Tour… "" 2019 NA commun… low
#> 4 Aceh Jaya Coast… 646c… Fish… "" 2019 NA commun… low
#> 5 Aceh Jaya Coast… a579… Aqua… "" 2019 NA commun… low
#> 6 Aceh Jaya Coast… dce8… Reha… "" 2019 NA commun… low
#> 7 Karimunjawa Nat… 8b90… Fish… "" 2005 0 commun… low
#> 8 Karimunjawa Nat… a7e2… Tour… "" 2005 NA commun… low
#> 9 Karimunjawa Nat… bd73… Reha… "" 2005 NA commun… low
#> 10 Copy of Karimun… 510a… Fish… "" 2005 0 <NA> low
#> # ℹ 20 more rows
#> # ℹ 10 more variables: open_access <lgl>, no_take <lgl>,
#> # access_restriction <lgl>, periodic_closure <lgl>, size_limits <lgl>,
#> # gear_restriction <lgl>, species_restriction <lgl>, notes <chr>,
#> # created_on <chr>, updated_on <chr>You can also access data on your projects’ Fish Belt, Benthic LIT, Benthic PIT, Bleaching, and Habitat Complexity methods. The details are in the following sections.
To access Fish Belt data for a project, use
mermaid_get_project_data() with
method = "fishbelt".
You can access individual observations (i.e., a record of each
observation) by setting data = "observations":
xpdc <- my_projects %>%
filter(name == "XPDC Kei Kecil 2018")
xpdc %>%
mermaid_get_project_data(method = "fishbelt", data = "observations")
#> # A tibble: 3,069 × 52
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 2 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 3 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 4 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 5 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 6 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 7 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 8 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 9 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 10 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> # ℹ 3,059 more rows
#> # ℹ 44 more variables: reef_exposure <chr>, reef_slope <chr>, tide <chr>,
#> # current <chr>, visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, transect_length <dbl>, …You can access sample units data, which are observations aggregated to the sample units level. Fish belt sample units contain total biomass in kg/ha per sample unit, by trophic group and by fish family:
xpdc %>%
mermaid_get_project_data("fishbelt", "sampleunits")
#> # A tibble: 246 × 64
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 2 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 3 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 4 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 5 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 6 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 7 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> 8 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> 9 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> 10 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> # ℹ 236 more rows
#> # ℹ 56 more variables: reef_exposure <chr>, reef_slope <chr>, tide <chr>,
#> # current <chr>, visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <chr>, depth <dbl>, transect_number <dbl>, label <lgl>, …And finally, sample events data, which are aggregated further, to the sample event level. Fish belt sample events contain mean total biomass in kg/ha per sample event, by trophic group and by fish family, as well as standard deviations:
xpdc_sample_events <- xpdc %>%
mermaid_get_project_data("fishbelt", "sampleevents")
xpdc_sample_events
#> # A tibble: 46 × 79
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 2 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> 3 XPDC Kei Kecil 20… NA Indone… KE04 -5.58 132. fringing crest
#> 4 XPDC Kei Kecil 20… NA Indone… KE05 -5.47 133. fringing crest
#> 5 XPDC Kei Kecil 20… NA Indone… KE06 -5.52 132. fringing crest
#> 6 XPDC Kei Kecil 20… NA Indone… KE07 -5.57 133. fringing crest
#> 7 XPDC Kei Kecil 20… NA Indone… KE08 -5.55 133. fringing crest
#> 8 XPDC Kei Kecil 20… NA Indone… KE09 -5.60 133. fringing fore reef
#> 9 XPDC Kei Kecil 20… NA Indone… KE10 -5.57 133. fringing crest
#> 10 XPDC Kei Kecil 20… NA Indone… KE11 -5.59 133. fringing crest
#> # ℹ 36 more rows
#> # ℹ 71 more variables: reef_exposure <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, management <chr>, management_secondary <chr>,
#> # management_est_year <lgl>, management_size <lgl>, management_parties <lgl>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # depth_avg <dbl>, depth_sd <dbl>, biomass_kgha_avg <dbl>,
#> # biomass_kgha_sd <dbl>, biomass_kgha_trophic_group_avg_omnivore <dbl>, …To access Benthic LIT data, use
mermaid_get_project_data() with
method = "benthiclit".
mozambique <- my_projects %>%
filter(name == "WCS Mozambique Coral Reef Monitoring")
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "observations")
#> # A tibble: 1,569 × 41
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 2 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 3 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 4 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 5 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 6 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 7 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 8 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 9 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 10 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> # ℹ 1,559 more rows
#> # ℹ 33 more variables: reef_exposure <chr>, reef_slope <lgl>, tide <chr>,
#> # current <lgl>, visibility <lgl>, relative_depth <lgl>, management <chr>,
#> # management_secondary <lgl>, management_est_year <dbl>,
#> # management_size <lgl>, management_parties <chr>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, transect_number <dbl>, …You can access sample units and sample events the same way.
For Benthic LIT, sample units contain percent cover per sample unit, by benthic category. Sample events contain mean percent cover per sample event, by benthic category, and standard deviations for these values:
mozambique %>%
mermaid_get_project_data(method = "benthiclit", data = "sampleunits")
#> # A tibble: 63 × 50
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 2 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 3 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 4 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 5 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 6 WCS Mozambique Co… WCS … Mozamb… Barr… -26.0 32.9 barrier back reef
#> 7 WCS Mozambique Co… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef
#> 8 WCS Mozambique Co… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef
#> 9 WCS Mozambique Co… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef
#> 10 WCS Mozambique Co… WCS … Mozamb… Barr… -26.1 32.9 barrier back reef
#> # ℹ 53 more rows
#> # ℹ 42 more variables: reef_exposure <chr>, reef_slope <lgl>, tide <chr>,
#> # current <lgl>, visibility <lgl>, relative_depth <lgl>, management <chr>,
#> # management_secondary <lgl>, management_est_year <dbl>,
#> # management_size <lgl>, management_parties <chr>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, transect_number <dbl>, …To access Benthic LIT data, change method to
“benthicpit”:
xpdc %>%
mermaid_get_project_data(method = "benthicpit", data = "observations")
#> # A tibble: 11,100 × 46
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 2 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 3 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 4 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 5 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 6 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 7 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 8 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 9 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 10 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> # ℹ 11,090 more rows
#> # ℹ 38 more variables: reef_exposure <chr>, reef_slope <chr>, tide <chr>,
#> # current <chr>, visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, transect_number <dbl>, …You can access sample units and sample events the same way, and the data format is the same as Benthic LIT.
You can return both sample units and sample events by setting the
data argument. This will return a list of two data frames:
one containing sample units, and the other sample events.
xpdc_sample_units_events <- xpdc %>%
mermaid_get_project_data(method = "benthicpit", data = c("sampleunits", "sampleevents"))
names(xpdc_sample_units_events)
#> [1] "sampleunits" "sampleevents"
xpdc_sample_units_events[["sampleunits"]]
#> # A tibble: 111 × 55
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 2 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 3 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 4 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> 5 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> 6 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> 7 XPDC Kei Kecil 20… NA Indone… KE04 -5.58 132. fringing crest
#> 8 XPDC Kei Kecil 20… NA Indone… KE04 -5.58 132. fringing crest
#> 9 XPDC Kei Kecil 20… NA Indone… KE04 -5.58 132. fringing crest
#> 10 XPDC Kei Kecil 20… NA Indone… KE05 -5.47 133. fringing crest
#> # ℹ 101 more rows
#> # ℹ 47 more variables: reef_exposure <chr>, reef_slope <chr>, tide <chr>,
#> # current <chr>, visibility <chr>, relative_depth <chr>, management <chr>,
#> # management_secondary <chr>, management_est_year <lgl>,
#> # management_size <lgl>, management_parties <lgl>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, transect_number <dbl>, …To access Bleaching data, set method to “bleaching”.
There are two types of observations data for the Bleaching method:
Colonies Bleached and Percent Cover. These are both returned when
pulling observations data, in a list:
bleaching_obs <- mozambique %>%
mermaid_get_project_data("bleaching", "observations")
names(bleaching_obs)
#> [1] "colonies_bleached" "percent_cover"
bleaching_obs[["colonies_bleached"]]
#> # A tibble: 1,814 × 43
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 2 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 3 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 4 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 5 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 6 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 7 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 8 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 9 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 10 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> # ℹ 1,804 more rows
#> # ℹ 35 more variables: reef_exposure <chr>, tide <lgl>, current <lgl>,
#> # visibility <lgl>, relative_depth <lgl>, management <chr>,
#> # management_secondary <lgl>, management_est_year <dbl>,
#> # management_size <lgl>, management_parties <chr>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # sample_time <time>, depth <dbl>, quadrat_size <dbl>, label <chr>, …The sample units and sample events data contain summaries of both Colonies Bleached and Percent Cover:
mozambique %>%
mermaid_get_project_data("bleaching", "sampleevents")
#> # A tibble: 62 × 49
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 2 WCS Mozambique Co… WCS … Mozamb… Baby… -11.0 40.7 fringing fore reef
#> 3 WCS Mozambique Co… WCS … Mozamb… Balu… -22.0 35.5 patch fore reef
#> 4 WCS Mozambique Co… WCS … Mozamb… Dos … -12.1 40.6 lagoon back reef
#> 5 WCS Mozambique Co… WCS … Mozamb… Fing… -12.9 40.6 fringing fore reef
#> 6 WCS Mozambique Co… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef
#> 7 WCS Mozambique Co… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef
#> 8 WCS Mozambique Co… WCS … Mozamb… Kisi… -11.0 40.7 lagoon back reef
#> 9 WCS Mozambique Co… WCS … Mozamb… Libe… -14.5 40.7 fringing back reef
#> 10 WCS Mozambique Co… WCS … Mozamb… Ligh… -12.3 40.6 fringing fore reef
#> # ℹ 52 more rows
#> # ℹ 41 more variables: reef_exposure <chr>, tide <lgl>, current <lgl>,
#> # visibility <lgl>, management <chr>, management_secondary <lgl>,
#> # management_est_year <dbl>, management_size <lgl>, management_parties <chr>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # depth_avg <dbl>, depth_sd <dbl>, quadrat_size_avg <dbl>,
#> # count_total_avg <dbl>, count_total_sd <dbl>, count_genera_avg <dbl>, …Finally, to access Habitat Complexity data, set method
to “habitatcomplexity”. As with all other methods, you can access
observations, sample units, and sample events:
xpdc %>%
mermaid_get_project_data("habitatcomplexity", "sampleevents")
#> # A tibble: 2 × 33
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 XPDC Kei Kecil 2018 NA Indone… KE22 -5.85 133. fringing fore reef
#> 2 XPDC Kei Kecil 2018 NA Indone… KE24 -5.93 133. fringing fore reef
#> # ℹ 25 more variables: reef_exposure <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, management <chr>, management_secondary <chr>,
#> # management_est_year <lgl>, management_size <lgl>, management_parties <lgl>,
#> # management_compliance <lgl>, management_rules <chr>, sample_date <date>,
#> # depth_avg <dbl>, depth_sd <dbl>, score_avg_avg <dbl>, score_avg_sd <dbl>,
#> # data_policy_habitatcomplexity <chr>, project_notes <chr>, site_notes <lgl>,
#> # management_notes <lgl>, …To pull data for both fish belt and benthic PIT methods, you can set
method to include both.
xpdc_sample_events <- xpdc %>%
mermaid_get_project_data(method = c("fishbelt", "benthicpit"), data = "sampleevents")The result is a list of data frames, containing sample events for both fish belt and benthic PIT methods:
names(xpdc_sample_events)
#> [1] "fishbelt" "benthicpit"
xpdc_sample_events[["benthicpit"]]
#> # A tibble: 38 × 63
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <lgl> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 XPDC Kei Kecil 20… NA Indone… KE02 -5.44 133. fringing crest
#> 2 XPDC Kei Kecil 20… NA Indone… KE03 -5.61 132. fringing crest
#> 3 XPDC Kei Kecil 20… NA Indone… KE04 -5.58 132. fringing crest
#> 4 XPDC Kei Kecil 20… NA Indone… KE05 -5.47 133. fringing crest
#> 5 XPDC Kei Kecil 20… NA Indone… KE06 -5.52 132. fringing crest
#> 6 XPDC Kei Kecil 20… NA Indone… KE07 -5.57 133. fringing crest
#> 7 XPDC Kei Kecil 20… NA Indone… KE08 -5.55 133. fringing crest
#> 8 XPDC Kei Kecil 20… NA Indone… KE09 -5.60 133. fringing fore reef
#> 9 XPDC Kei Kecil 20… NA Indone… KE10 -5.57 133. fringing crest
#> 10 XPDC Kei Kecil 20… NA Indone… KE11 -5.59 133. fringing crest
#> # ℹ 28 more rows
#> # ℹ 55 more variables: reef_exposure <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, management <chr>, management_secondary <chr>,
#> # management_est_year <lgl>, management_size <lgl>, management_parties <lgl>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # depth_avg <dbl>, depth_sd <dbl>,
#> # percent_cover_benthic_category_avg_sand <dbl>, …Alternatively, you can set method to “all” to pull for
all methods! Similarly, you can set data to “all” to pull
all types of data:
all_project_data <- xpdc %>%
mermaid_get_project_data(method = "all", data = "all", limit = 1)
names(all_project_data)
#> [1] "fishbelt" "benthiclit" "benthicpit"
#> [4] "benthicpqt" "bleaching" "habitatcomplexity"
names(all_project_data[["benthicpit"]])
#> [1] "observations" "sampleunits" "sampleevents"Pulling data for multiple projects is the exact same, except there
will be an additional “project” column at the beginning to distinguish
which projects the data comes from. Recall that my_projects
contains six projects:
my_projects
#> # A tibble: 19 × 15
#> id name countries num_sites tags notes status data_policy_beltfish
#> <chr> <chr> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 02e6915c-1… TWP … Indonesia 14 "WCS… "" Open Private
#> 2 170e7182-7… 2018… Fiji 10 "WCS… "Thi… Open Private
#> 3 173c2353-3… Copy… Fiji 8 "WCS… "Nam… Open Public Summary
#> 4 1fbdb9ea-9… a2 Canada, … 9 "WWF… "Nam… Open Private
#> 5 2c0c9857-b… Shar… Canada, … 27 "" "dhf… Open Public Summary
#> 6 2d6cee25-c… WCS … Mozambiq… 74 "WCS… "Dat… Open Private
#> 7 3a9ecb7c-f… Aceh… Indonesia 18 "WCS… "" Open Private
#> 8 4080679f-1… Mada… Madagasc… 74 "WCS… "MAC… Open Private
#> 9 4d23d2a1-7… Mada… Madagasc… 16 "WCS… "Mon… Open Public Summary
#> 10 507d1af9-e… Kari… Indonesia 43 "WCS… "" Open Private
#> 11 5679ef3d-b… Mada… Madagasc… 33 "WCS… "" Open Public Summary
#> 12 5f13e6dc-4… Copy… Indonesia 43 "WCS… "" Open Public Summary
#> 13 75ef7a5a-c… Kubu… Fiji 78 "WCS… "" Open Private
#> 14 7a6bfd69-6… Copy… Belize 31 "WCS… "" Open Public Summary
#> 15 9de82789-c… XPDC… Indonesia 37 "" "XPD… Open Private
#> 16 a1b7ff1f-8… Grea… Fiji 76 "Uni… "" Open Private
#> 17 bacd3529-e… Beli… Belize, … 35 "WCS… "" Open Public Summary
#> 18 d065cba4-e… 2019… Fiji 31 "WCS… "Ble… Open Private
#> 19 e1efb1e0-0… 2016… Fiji 8 "WCS… "Nam… Open Private
#> # ℹ 7 more variables: data_policy_benthiclit <chr>,
#> # data_policy_benthicpit <chr>, data_policy_benthicpqt <chr>,
#> # data_policy_habitatcomplexity <chr>, data_policy_bleachingqc <chr>,
#> # created_on <chr>, updated_on <chr>
my_projects %>%
mermaid_get_project_data("fishbelt", "sampleevents", limit = 1)
#> # A tibble: 13 × 157
#> project tags country site latitude longitude reef_type reef_zone
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 TWP Gili Sulat La… WCS … Indone… Peda… -8.28 117. fringing crest
#> 2 2018_Vatu-i-Ra re… WCS … Fiji VIR1 -17.3 178. barrier fore reef
#> 3 Sharla test <NA> Indone… 1201 -2.02 134. fringing fore reef
#> 4 WCS Mozambique Co… WCS … Mozamb… Aqua… -21.8 35.5 barrier back reef
#> 5 Aceh Jaya Coastal… WCS … Indone… Abah… 4.99 95.4 fringing fore reef
#> 6 Madagascar WCS MA… WCS … Madaga… Kisi… -13.6 48.1 fringing fore reef
#> 7 Karimunjawa Natio… WCS … Indone… Batu… -5.81 110. fringing back reef
#> 8 Madagascar Baie d… WCS … Madaga… Anta… -16.4 49.8 fringing fore reef
#> 9 Kubulau 2009-2011 WCS … Fiji C13 -17.0 179. barrier fore reef
#> 10 XPDC Kei Kecil 20… <NA> Indone… KE02 -5.44 133. fringing crest
#> 11 Great Sea Reef 20… Fiji… Fiji BA02 -17.4 178. atoll back reef
#> 12 Belize Glover's A… WCS … Belize CZFR1 16.7 -87.8 atoll fore reef
#> 13 2016_Namena Marin… WCS … Fiji C3 -17.1 179. barrier fore reef
#> # ℹ 149 more variables: reef_exposure <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, management <chr>, management_secondary <chr>,
#> # management_est_year <dbl>, management_size <dbl>, management_parties <chr>,
#> # management_compliance <chr>, management_rules <chr>, sample_date <date>,
#> # depth_avg <dbl>, depth_sd <dbl>, biomass_kgha_avg <dbl>,
#> # biomass_kgha_sd <dbl>, biomass_kgha_trophic_group_avg_omnivore <dbl>,
#> # biomass_kgha_trophic_group_avg_piscivore <dbl>, …Note the limit argument here, which just limits the data
pulled to one record (per project, method, and data combination). This
is useful if you want to get a preview of what your data will look like
without having to pull it all in.
Prior to mermaidr 0.7.0, covariates were automatically
included in all mermaid_get_project_data() function calls.
Now, to access covariates, include covariates = TRUE in the
function call:
my_projects %>%
head(1) %>%
mermaid_get_project_data("fishbelt", "sampleevents", limit = 1, covariates = TRUE)
#> # A tibble: 1 × 87
#> site_id project tags country site latitude longitude reef_type reef_zone
#> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr>
#> 1 369a0b3c-1… TWP Gi… WCS … Indone… Peda… -8.28 117. fringing crest
#> # ℹ 78 more variables: reef_exposure <chr>, tide <chr>, current <chr>,
#> # visibility <chr>, aca_geomorphic <chr>, aca_benthic <chr>,
#> # andrello_grav_nc <dbl>, andrello_sediment <dbl>, andrello_nutrient <dbl>,
#> # andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, management <chr>, …You can also access covariates at the site level, using
mermaid_get_project_sites() with
covariates = TRUE:
my_projects %>%
mermaid_get_project_sites(covariates = TRUE)
#> # A tibble: 665 × 27
#> project id name notes latitude longitude country reef_type reef_zone
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Great Sea R… 0235… BA09 "" -17.4 178. Fiji atoll back reef
#> 2 Great Sea R… 0879… BA16 "" -17.2 178. Fiji atoll back reef
#> 3 Great Sea R… 1925… BA15 "" -17.2 178. Fiji atoll back reef
#> 4 Great Sea R… 19e6… YA02 "" -17.0 177. Fiji atoll back reef
#> 5 Great Sea R… 20ae… BA11 "" -17.3 178. Fiji atoll back reef
#> 6 Great Sea R… 2af4… BA12 "" -17.3 178. Fiji atoll back reef
#> 7 Great Sea R… 2f08… BA10 "" -17.3 178. Fiji atoll back reef
#> 8 Great Sea R… 364f… YA08 "" -17.0 177. Fiji atoll back reef
#> 9 Great Sea R… 3888… YA03 "" -16.9 177. Fiji atoll back reef
#> 10 Great Sea R… 3ceb… LW07 "Adj… -17.6 177. Fiji atoll back reef
#> # ℹ 655 more rows
#> # ℹ 18 more variables: exposure <chr>, aca_geomorphic <chr>, aca_benthic <chr>,
#> # andrello_grav_nc <dbl>, andrello_sediment <dbl>, andrello_nutrient <dbl>,
#> # andrello_pop_count <dbl>, andrello_num_ports <dbl>,
#> # andrello_reef_value <dbl>, andrello_cumul_score <dbl>, beyer_score <dbl>,
#> # beyer_scorecn <dbl>, beyer_scorecy <dbl>, beyer_scorepfc <dbl>,
#> # beyer_scoreth <dbl>, beyer_scoretr <dbl>, created_on <chr>, …